CANCELLED - Patient-specific long-term prediction of transcatheter edge-to-edge mitral valve repair

Natalie Simonian, Michael S Sacks

University of Texas at Austin, United States of America

Functional assessment of patients with mitral valve defect augmented by biomechanical modeling: Contractile reserve of the heart and in-silico valve repair

Hoang Nguyen¹, Maria Gusseva¹, Sanja Dzelebdzic^1,2, Gerald Greil¹, Tarique Hussain¹, Radomir Chabiniok¹

1: UT Southwestern Medical Center Dallas, Texas, USA; 2: The University of Utah, Salt Lak City, UT, USA

Model reduction for fluid-solid simulations to assess hemodynamics of mitral valve regurgitation and repair

Marc Hirschvogel¹, Mia Bonini³, Maximilian Balmus², David Nordsletten^3,4

1: MOX, Dipartimento di Matematica, Politecnico di Milano, Milan, Italy; 2: TRIC-DT, The Alan Turing Institute, National Heart and Lung Institute, Imperial College London, London, UK; 3: Department of Biomedical Engineering, University of Michigan, Ann Arbor, USA; 4: Department of Cardiac Surgery, University of Michigan, Ann Arbor, USA

Influence of valve shape on mitral valve hemodynamics: An in-silico study

Juliana Franz^1,2, Jan Brüning^1,2, Leonid Goubergrits^1,2, Alexandra Groth³, Titus Kühne^1,2, Valentina Lavezzo⁴, Irina Waechter-Stehle³, Katharina Vellguth^1,2

1: Charité - Universitätsmedizin Berlin, Germany; 2: Deutsches Herzzentrum der Charité, Institute of Computer-assisted Cardiovascular Medicine, Germany; 3: Philips Innovation Technologies, Hamburg, Germany; 4: Philips, Eindhoven, The Netherlands

Synthetic cohort of mitral valve anatomies based on statistical shape modeling

Katharina Vellguth^1,2, Lukas Obermeier^1,2, Jonathan Nestmann³, Serdar Akansel^1,4, Leonid Goubergrits^1,2

1: Charité - Universitätsmedizin Berlin, Germany; 2: Deutsches Herzzentrum der Charité, Institute of Computer-assisted Cardiovascular Medicine, Germany; 3: ETH Zürich, Department of Information Technology and Electrical Engineering, Switzerland; 4: Deutsches Herzzentrum der Charité, Department of Cardiothoracic and Vascular Surgery, Germany

Modelling the electrophysiology of the non-pregnant uterus: From interconnected cells to organ

Alys Clark, Mathias Roesler, Shawn Means, Amy Garrett, Leo Cheng

University of Auckland, New Zealand

Computational modeling of the effect of laser tissue soldering on colonic motility

René Thierry Djoumessi¹, Pietro Lenarda¹, Pietro Alduini², Marco Paggi¹, Alessio Gizzi³

1: IMT School for Advanced Studies Lucca, Italy; 2: Hospital of Saint Luca, Italy; 3: Università Campus Bio-Medico di Roma, Italy

Neural stimulation modifies the organ-scale coordination of rat gastric slow waves

Omkar N. Athavale, Recep Avci, Alys R. Clark, Leo K. Cheng, Peng Du

University of Auckland, New Zealand

Computational modelling of the human gastric peristalsis

Maire Salina Henke¹, Sebastian Brandstaeter², Alessio Gizzi³, Roland Can Aydin^1,4, Christian Johannes Cyron^1,4

1: Institute for Continuum and Material Mechanics, Hamburg University of Technology, Germany; 2: Institute for Mathematics and Computer-Based Simulation, University of the Bundeswehr Munich, Germany; 3: Department of Engineering, Campus Bio-Medico University of Rome, Italy; 4: Institute of Material Systems Modeling, Helmholtz-Zentrum Hereon, Germany

Exploring host-microbiota interactions through mechanistic modelling: Insights into diet impact on beneficial symbiosis resilience in the human gut

Marie Haghebaert^1,2,3, Béatrice Laroche^1,2, Lorenzo Sala^1,2, Stanislas Mondot⁴, Joel Doré^4,5

1: Université Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, 78350, France; 2: Université Paris-Saclay, INRIA, MUSCA, Palaiseau, 91120, France; 3: Université Paris-Saclay, INRIA, SIMBIOTX, Palaiseau, 91120, France; 4: Micalis Institute, INRAE, AgroParisTech, University Paris-Saclay, Jouy-en-Josas, 78350, France; 5: Université Paris-Saclay, MGP, INRAE, Jouy-en-Josas, 78350, France

Predictive modelling of renal circulation hemodynamic outcomes in hypertensive and diabetic kidney disease

Ning Wang^1,2, Ivan Benemerito^1,2, Steven Sourbron^1,3, Alberto Marzo^1,2

1: INSIGNEO Institute for in silico medicine, The University of Sheffield, UK; 2: Department of Mechanical Engineering, The University of Sheffield, UK; 3: School of Medicine and Population Health, The University of Sheffield, UK

Patient-specific TAVI thrombosis modelling: Insights from haemodynamic analysis

Maria Isabel Pons Vidal, Harriet Hurrell, Tiffany Patterson, Jack Lee

King's College of London, United Kingdom

Unveiling the relation between aortic shape and calcification in population with aortic stenosis: Towards better management of TAVI patients

Raphael Sivera¹, Ebba Montgomery-Liljeroth¹, Andrew Cook¹, Silvia Schievano¹, Kush Patel², Claudio Capelli¹

1: Institute of Cardiovascular Science, University College London, London, UK; 2: Bart’s Heart Centre, St Bartholomew’s Hospital, London, UK

Identify transcatheter aortic valve implantation degeneration using computational hemodynamic scores

Luca Crugnola¹, Laura Fusini^2,1, Ivan Fumagalli¹, Giulia Luraghi¹, Alberto Redaelli¹, Gianluca Pontone^2,3, Christian Vergara¹

1: Politecnico di Milano, Milan, Italy; 2: Centro Cardiologico Monzino IRCSS, Milan, Italy; 3: Università degli Studi di Milano, Milan, Italy

Predicting transcatheter aortic valve implantation procedural outcomes through the development and validation of patient-specific simulations

Benedetta Grossi^1,2, Giulia Luraghi¹, Anna Ramella¹, Ottavia Cozzi^2,3, Sara Barati¹, Alessandro Villaschi^2,3, Josè Felix Rodriguez Matas¹, Gianluigi Condorelli^2,3, Giulio Stefanini^2,3, Francesco Migliavacca¹

1: Department of Chemistry, Materials and Chemical Engineering, Politecnico di Milano, Milan, Italy; 2: Department of Biomedical Sciences, Humanitas University, Milan, Italy; 3: Humanitas Research Hospital, Milan, Italy

Virtual cohort generation for in silico trials of transcatheter aortic valve implantation

Sabine Verstraeten¹, Doris Thissen¹, Martijn Hoeijmakers², Frans van de Vosse¹, Wouter Huberts¹

1: Eindhoven University of Technology, Netherlands, The; 2: ANSYS, The Netherlands

Simulation workflow for transcatheter aortic valve replacements: From crimp and deployment to fluid-structure interaction

Nils Karajan¹, Facundo Del Pin², Rodrigo Paz², Sophie Collin², Marco Sensale², Martijn Hoeijmakers², Michel Rochette², Mark Palmer²

1: DYNAmore, An Ansys Company, Germany; 2: Ansys, Inc.

HPC in Biomechanics - Challenges, Current Research and Future Opportunities

Johannes Gebert, Benjamin Schnabel

High-Performance Computing Center Stuttgart, Germany

A user interface to facilitate visualization and integration of predictions for mechanical femur strength.

Massimiliano Mercuri¹, Filippo Nardini², Cristina Curreli³, Antonino A. La Mattina³, Sabato Mellone², Marco Viceconti^1,3

1: Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.; 2: Department of Electrical, Electronic and Information Engineering, University of Bologna, 40126 Bologna, Italy; 3: Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy.

Enhancing large-scale cohort simulations through integrated HPC infrastructure and model execution environment

Karol Zając¹, Taras Zhyhulin¹, Piotr Nowakowski^1,2, Jan Meizner^1,2, Bartosz Baliś¹, Konrad Czerepak¹, Marek Kasztelnik², Piotr Połeć², Sara Oliviero³, Maciej Malawski^1,2

1: Sano - Centre for Computational Personalized Medicine, Kraków, Poland; 2: ACC Cyfronet AGH, Kraków, Poland; 3: Department of Industrial Engineering, Alma Mater Studiorum, University of Bologna, Bologna, Italy

Code verification of contact analysis using a micro-finite-element solver

Frederik Max Trommer^1,2, Pinaki Bhattacharya^1,2

1: Department of Mechanical Engineering, University of Sheffield, United Kingdom; 2: Insigneo Institute for in silico Medicine

Classification of retinal vein occlusion and diabetic macular edema with deep learning in OCT images

Guilherme Barbosa¹, Eduardo da Silva Carvalho¹, Ana Guerra¹, Nilza Ramião¹, Marco Parente^1,2, Sónia Torres-Costa^3,4, Manuel Falcão^3,4

1: INEGI - Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal; 2: DEMec - Department of Mechanical Engineering, Faculty of Engineering of University of Porto (FEUP), Porto, Portugal; 3: Surgery and Physiology Department, Faculty of Medicine of University of Porto (FMU; 4: Ophthalmology Department, ULS São Joao, Porto, Portugal

Classification of glenoid bone loss patterns using statistical shape modelling

Harnoor Saini¹, Julie Kim¹, Marc Hirner², Sumit Raniga³, Desmond Bokor³, Thor Besier¹

1: Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; 2: Northland Orthopaedic Clinic, Whangarei, New Zealand; 3: Shoulder and Elbow Clinic, Macquarie University, Sydney, NSW, Australia

Strain analysis in the right ventricular outflow tract using non-parametric deformable shape modelling

Liam David Swanson^1,2, Raphael Sivera^1,2, Nicholas M. Jacobson³, Claudio Capelli^1,2, Catalina Vargas-Acevedo^4,5, Gareth J. Morgan^5,6,7, Silvia Schievano^1,2

1: Institute of Cardiovascular Sciences, University College London, London, United Kingdom; 2: Great Ormond Street Children’s Hospital, London, United Kingdom; 3: College of Engineering, Design and Computing, University of Colorado, Aurora, CO, United States of America; 4: Department of Pediatric Cardiology, University of Colorado, Aurora, CO, United States of America; 5: The Heart Institute, Children's Hospital Colorado, Aurora, CO, United States of America; 6: School of Medicine, Anschutz Medical Campus, University of Colorado, Aurora, CO, United States of America; 7: Department of Cardiology, University of Colorado Hospital, Aurora, CO, United States of America

Hexahedral mesh fitting using scaffolds and statistical shape modelling to reproduce the cortical bone morphology of the femur

Ted Yeung, Thor Besier, Peter Hunter, Vickie Shim

Auckland Bioengineering Institute, University of Auckland, New Zealand

Development of a statistical shape and density model of the paediatric femur for personalised FE models in children

Yidan Xu, Laura Carman, Thor Besier, Julie Choisne

Auckland Bioengineering Institute, The University of Auckland, New Zealand

Generation of digital genetic twins satisfying utility and privacy metrics for robust post-hoc analyses

Igor Faddeenkov¹, Olivia Rousseau¹, Sonia Bourguiba-Hachemi¹, Sophie Limou^1,2, Nicolas Vince¹, Pierre-Antoine Gourraud^1,3

1: Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, F-44000 Nantes, France; 2: Ecole Centrale de Nantes, F-44300 Nantes, France; 3: Nantes Université, CHU Nantes, PHU11: Santé Publique, Clinique des données, INSERM CIC 1413, F-44000 Nantes, France

Domain adaptation methods for emotion and pain recognition via synthetic data

Jonas Nasimzada¹, Constantin Seibold², Alina Roitberg¹

1: University of Stuttgart, Germany; 2: University Medicine Essen, Germany

Improved patient classification from 2D cardiac ultrasound using multi-modal transfer learning

Debbie Zhao¹, Joshua R. Dillon¹, Gina M. Quill¹, Bram W. M. Geven^1,2, Stephen A. Creamer¹, Edward Ferdian¹, Vicky Y. Wang¹, Thiranja P. Babarenda Gamage¹, Timothy M. Sutton³, Boris S. Lowe⁴, Malcolm E. Legget⁵, Nicola C. Edwards^4,5, Robert N. Doughty^4,5, Alistair A. Young⁶, Martyn P. Nash⁷

1: Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand; 2: Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 3: Counties Manukau Health Cardiology, Middlemore Hospital, Auckland, New Zealand; 4: Green Lane Cardiovascular Service, Auckland City Hospital, Auckland, New Zealand; 5: Department of Medicine, University of Auckland, Auckland, New Zealand; 6: School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom; 7: Department of Engineering Science and Biomedical Engineering, University of Auckland, Auckland, New Zealand

Bayesian inversion enables personalised septic shock treatment guided by noisy arterial pressure waveforms

Finneas JR Catling^1,2, Kim H Parker¹, Alun D Hughes², Steve Harris², Rebecca J Shipley², Anthony C Gordon¹

1: Imperial College London, London, United Kingdom; 2: University College London, London, United Kingdom

Enhancing ECMO device development through machine-learned virtual patient data

Micha Landoll^1,2,3, Yifei Huang¹, Ulrich Steinseifer¹, Stephan Strassmann², Christian Karagiannidis², Michael Neidlin¹

1: Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, Helmholtz Institute, RWTH Aachen University, Aachen, Germany; 2: ARDS and ECMO Centre Cologne-Merheim, Dept. of Pneumology and Critical Care Medicine, Kliniken der Stadt Köln gGmbH, Witten/Herdecke University, Cologne, Germany; 3: Institute for Computational Biomedicine II, University Hospital Aachen, RWTH Aachen University, Aachen, Germany

Towards an in silico clinical trial on the use of fractional flow reserve based on a data-driven modeling approach

Pjotr Hilhorst¹, Sabine Verstraeten¹, Frans van de Vosse¹, Marcel van 't Veer^1,2, Pim Tonino², Wouter Huberts¹

1: Eindhoven University of Technology, Netherlands, The; 2: Catharina Hospital Eindhoven, Netherlands, The

Predicting ventricular tachycardia, taking time into the equations

Carlijn Buck¹, Marloes de Winter¹, Anouk de Lepper², Marcel van 't Veer², Wouter Huberts¹, Frans van de Vosse¹, Lukas Dekker²

1: Eindhoven University of Technology, the Netherlands; 2: Catharina Hospital Eindhoven, the Netherlands

Patient-specific hemodynamic effects of acute exercise in hypertensive subjects and controls revealed by 4D flow MRI and cardiovascular modeling

Kajsa Tunedal^1,2, Valentin Kindesjö¹, Federica Viola^2,3, Karin Rådholm³, Carl-Johan Carlhäll^2,3,4, Gunnar Cedersund^1,2, Tino Ebbers^2,3

1: Department of Biomedical Engineering, Linköping University, Linköping, Sweden; 2: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden; 3: Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden; 4: Department of Clinical Physiology in Linköping, and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden